Many digital capture devices are capable of capturing video as well as still images. Managing digital video content, however, can be a difficult task. Videos are often represented visually with a thumbnail image of the first frame of the video. This may not provide much insight into the content of the video. Determining if a specific event is contained in a given video often requires viewing the entire video. For a lengthy video, a user may prefer to be able to get a quick summary of the video without having to view the video in its entirety.
Digital videos can also present practical problems from a sharing perspective. Many digital capture devices record video at 30 or 60 frames per second, at spatial resolutions as high as 1920×1080 pixels. Even when compressed, the amount of data generated can make it impractical to share even relatively short videos.
Video editing software can be used to manually summarize a video into a shorter version that can be shared more easily. Manual video editing can be a lengthy, laborious process, however, and many users are not interested in manual editing. Automatic video summarization algorithms exist as well. These solutions start with a captured video as input, and analyze the video to determine a video summary. U.S. Pat. No. 5,995,095 to Ratakonda, entitled “Method for hierarchical summarization and browsing of digital video,” discloses a method for generating a hierarchical summary based on key-frames of a video sequence. U.S. Pat. No. 7,035,435 to Li et al., entitled “Scalable video summarization and navigation system and method,” describes a method for assigning an importance value to each scene, shot and frame in a video, and using the importance values to determine key frames for a video summary. U.S. Pat. No. 7,483,618 to Edwards et al., entitled “Automatic editing of a visual recording to eliminate content of unacceptably low quality and/or very little or no interest,” discloses a method for determining a video summary in which content of low quality or little interest is eliminated from the video.
Automatic video summarization algorithms are very complex, however, as it is necessary to decode the video to perform the analysis required to determine the video summary. Thus it is not possible on a digital capture device to immediately view a video summary corresponding to a just-captured video. This shortcoming makes it difficult to facilitate quick review and sharing of captured videos.
When creating a video summary, it is often desirable to have a specific feature within the summary. The video summary is created to contain some or all of the video content in which a feature is present. Examples of such features can include people, pets, events, locations, activities or objects. Manually creating such a tailored video summary can be a tedious process. Using desktop software to generate such a tailored video summary prevents the ability to quickly review and share video summaries.
It would thus be desirable to provide systems and methods for computing a video summary in a digital capture device. In particular, it would be desirable to provide solutions that allow a video summary to be generated on a digital capture device with minimal delay at the completion of video capture. Also, it would be desirable to provide a video summary that contains a user-specified feature.